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Artificial Intelligence for IoT Cookbook

You're reading from   Artificial Intelligence for IoT Cookbook Over 70 recipes for building AI solutions for smart homes, industrial IoT, and smart cities

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781838981983
Length 260 pages
Edition 1st Edition
Languages
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Author (1):
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Michael Roshak Michael Roshak
Author Profile Icon Michael Roshak
Michael Roshak
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Table of Contents (11) Chapters Close

Preface 1. Setting Up the IoT and AI Environment 2. Handling Data FREE CHAPTER 3. Machine Learning for IoT 4. Deep Learning for Predictive Maintenance 5. Anomaly Detection 6. Computer Vision 7. NLP and Bots for Self-Ordering Kiosks 8. Optimizing with Microcontrollers and Pipelines 9. Deploying to the Edge 10. About Packt

Deploying mobile models

Many IoT scenarios require that you have a graphical user interface; that is, a high level of compute, Bluetooth, and Wi-Fi and a cellular network. Most modern cell phones have these. An inexpensive IoT device can talk to an app on a smartphone via Bluetooth and use that app to perform ML and talk to the cloud.

Using cell phones can cut the time to market for IoT devices. These devices can use a secure and easily updatable app to send data to the cloud. The portability of cell phones is an appeal but also a drawback. Having a device constantly communicating with the cloud can drain a cell phone's battery so that it lasts for as little as 8 hours. Because of this, companies often look to edge processing to perform compute tasks such as machine learning. This allows the device to send data less frequently.

How cell phones are used for IoT is ubiquitous. Companies such as Fitbit and Tile use low-power Bluetooth Low Energy (BLE) to send data to consumer cell phones...

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